saccofrancesco/deepshot
Jupyter NotebookMITactive
Health
AI-powered NBA game outcome predictor that uses advanced team stats and trend-based features to forecast winners and track model performance
Health Breakdown
Activity25
Community25
Maintenance15
Popularity25
#ai#basketball#data-science#feature-engineering#jupyter-notebook#machine-learning#model-evaluation#nba#nba-prediction#nba-predictions#open-source#pandas#predictive-modeling#python#scikit-learn#sports-analysts#sports-data#sports-prediction#time-series#xgboost
Should you contribute to saccofrancesco/deepshot?
saccofrancesco/deepshot has a FoundDev health score of 90/100, which puts it in the active-and-maintained tier. The maintainer team is shipping recently, issues are being closed, and a PR you open this week has a realistic chance of being reviewed.
Last push was 0 days ago — that signals an actively maintained project. New issues are likely to get a maintainer response within days. The project is written primarily in Jupyter Notebook, so prior Jupyter Notebook experience will shorten ramp-up.
Licensed under MIT, a standard OSI-approved license — safe to contribute to under normal employer IP policies.
Community
Jupyter NotebookMIT
active
0d ago
